Potential Use of Sweet Potato (Ipomoea batatas (L.) Lam.) to Suppress Three Invasive Plant Species in Agroecosystems (Ageratum conyzoides L., Bidens pilosa L., and Galinsoga parviflora Cav.)
Bibliographic record
Abstract
Sweet potato (Ipomoea batatas (L.) Lam.) is a logical candidate crop to suppress invasive plants, but additional information is needed to support its potential application as a suppressive ground cover. The current study utilized a de Wit replacement series incorporating five ratios of sweet potato grown in the field in combination with one of three invasive plants (Ageratum conyzoides L., Bidens pilosa L., and Galinsoga parviflora Cav.) in replicated 9 m2 plots. Stem length, total biomass, and leaf area were higher for monoculture-grown sweet potato than these parameters for any of the invasive plants grown in monoculture. In mixed culture, the plant height, branch, leaf, inflorescence, seed, and biomass of all invasive plants were suppressed by sweet potato. The relative yield parameter indicated that intraspecific competition was greater than interspecific competition for sweet potato, while the reverse was true for invasive species. The net photosynthetic rate was higher for sweet potato than for B. pilosa and G. parviflora but not A. conyzoides. Superoxide dismutase and peroxidase activities of each of the three invasive plants were reduced in mixture with sweet potato. Our results demonstrated that these three invasive plants were significantly suppressed by sweet potato competition due to the rapid growth and phenotypic plasticity of sweet potato.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".